Batch processing

Process multiple files efficiently.

Overview

Learn how to analyze multiple recordings in parallel while respecting rate limits.

Node.js example

import { Mappa } from "@mappa-ai/mappa-node";

const mappa = new Mappa({
  apiKey: process.env.MAPPA_API_KEY!,
});

const urls = [
  "https://example.com/recording1.mp3",
  "https://example.com/recording2.mp3",
  "https://example.com/recording3.mp3",
];

// Process in parallel with concurrency limit
async function processBatch(urls: string[], concurrency = 3) {
  const results = [];
  
  for (let i = 0; i < urls.length; i += concurrency) {
    const batch = urls.slice(i, i + concurrency);
    const promises = batch.map((url) =>
      mappa.reports.generateFromUrl({
        url,
        output: { template: "general_report" },
      })
    );
    
    const batchResults = await Promise.all(promises);
    results.push(...batchResults);
  }
  
  return results;
}

const reports = await processBatch(urls);

Python example

import asyncio
from mappa import AsyncMappa

mappa = AsyncMappa(api_key=os.environ["MAPPA_API_KEY"])

urls = [
    "https://example.com/recording1.mp3",
    "https://example.com/recording2.mp3",
    "https://example.com/recording3.mp3",
]

async def process_batch(urls, concurrency=3):
    semaphore = asyncio.Semaphore(concurrency)
    
    async def process_one(url):
        async with semaphore:
            return await mappa.reports.generate_from_url(
                url=url,
                output={"template": "general_report"},
            )
    
    return await asyncio.gather(*[process_one(url) for url in urls])

reports = asyncio.run(process_batch(urls))